29 KiB
29 KiB
Incremental Statistics
Standard library functions for computing statistics incrementally.
Usage
var ns = require( '@stdlib/stats/incr' );
ns
Standard library functions for computing statistics incrementally.
var incr = ns;
// returns {...}
incrapcorr( [mx, my] )
: compute a sample absolute Pearson product-moment correlation coefficient incrementally.incrcount()
: compute a count incrementally.incrcovariance( [mx, my] )
: compute an unbiased sample covariance incrementally.incrcovmat( out[, means] )
: compute an unbiased sample covariance matrix incrementally.incrcv( [mean] )
: compute the coefficient of variation (CV) incrementally.increwmean( alpha )
: compute an exponentially weighted mean incrementally.increwstdev( alpha )
: compute an exponentially weighted standard deviation incrementally.increwvariance( alpha )
: compute an exponentially weighted variance incrementally.incrgmean()
: compute a geometric mean incrementally.incrgrubbs( [options] )
: grubbs' test for outliers.incrhmean()
: compute a harmonic mean incrementally.incrkurtosis()
: compute a corrected sample excess kurtosis incrementally.incrmaape()
: compute the mean arctangent absolute percentage error (MAAPE) incrementally.incrmae()
: compute the mean absolute error (MAE) incrementally.incrmapcorr( window[, mx, my] )
: compute a moving sample absolute Pearson product-moment correlation coefficient incrementally.incrmape()
: compute the mean absolute percentage error (MAPE) incrementally.incrmax()
: compute a maximum value incrementally.incrmaxabs()
: compute a maximum absolute value incrementally.incrmcovariance( window[, mx, my] )
: compute a moving unbiased sample covariance incrementally.incrmcv( window[, mean] )
: compute a moving coefficient of variation (CV) incrementally.incrmda()
: compute the mean directional accuracy (MDA) incrementally.incrme()
: compute the mean error (ME) incrementally.incrmean()
: compute an arithmetic mean incrementally.incrmeanabs()
: compute an arithmetic mean of absolute values incrementally.incrmeanabs2()
: compute an arithmetic mean of squared absolute values incrementally.incrmeanstdev( [out] )
: compute an arithmetic mean and a corrected sample standard deviation incrementally.incrmeanvar( [out] )
: compute an arithmetic mean and an unbiased sample variance incrementally.incrmgmean( window )
: compute a moving geometric mean incrementally.incrmgrubbs( window[, options] )
: moving Grubbs' test for outliers.incrmhmean( window )
: compute a moving harmonic mean incrementally.incrmidrange()
: compute a mid-range incrementally.incrmin()
: compute a minimum value incrementally.incrminabs()
: compute a minimum absolute value incrementally.incrminmax( [out] )
: compute a minimum and maximum incrementally.incrminmaxabs( [out] )
: compute minimum and maximum absolute values incrementally.incrmmaape( window )
: compute a moving mean arctangent absolute percentage error (MAAPE) incrementally.incrmmae( window )
: compute a moving mean absolute error (MAE) incrementally.incrmmape( window )
: compute a moving mean absolute percentage error incrementally.incrmmax( window )
: compute a moving maximum value incrementally.incrmmaxabs( window )
: compute a moving maximum absolute value incrementally.incrmmda( window )
: compute a moving mean directional accuracy (MDA) incrementally.incrmme( window )
: compute a moving mean error (ME) incrementally.incrmmean( window )
: compute a moving arithmetic mean incrementally.incrmmeanabs( window )
: compute a moving arithmetic mean of absolute values incrementally.incrmmeanabs2( window )
: compute a moving arithmetic mean of squared absolute values incrementally.incrmmeanstdev( [out,] window )
: compute a moving arithmetic mean and corrected sample standard deviation incrementally.incrmmeanvar( [out,] window )
: compute a moving arithmetic mean and unbiased sample variance incrementally.incrmmidrange( window )
: compute a moving mid-range incrementally.incrmmin( window )
: compute a moving minimum value incrementally.incrmminabs( window )
: compute a moving minimum absolute value incrementally.incrmminmax( [out,] window )
: compute a moving minimum and maximum incrementally.incrmminmaxabs( [out,] window )
: compute moving minimum and maximum absolute values incrementally.incrmmpe( window )
: compute a moving mean percentage error (MPE) incrementally.incrmmse( window )
: compute a moving mean squared error (MSE) incrementally.incrmpcorr( window[, mx, my] )
: compute a moving sample Pearson product-moment correlation coefficient incrementally.incrmpcorr2( window[, mx, my] )
: compute a moving squared sample Pearson product-moment correlation coefficient incrementally.incrmpcorrdist( window[, mx, my] )
: compute a moving sample Pearson product-moment correlation distance incrementally.incrmpe()
: compute the mean percentage error (MPE) incrementally.incrmprod( window )
: compute a moving product incrementally.incrmrange( window )
: compute a moving range incrementally.incrmrmse( window )
: compute a moving root mean squared error (RMSE) incrementally.incrmrss( window )
: compute a moving residual sum of squares (RSS) incrementally.incrmse()
: compute the mean squared error (MSE) incrementally.incrmstdev( window[, mean] )
: compute a moving corrected sample standard deviation incrementally.incrmsum( window )
: compute a moving sum incrementally.incrmsumabs( window )
: compute a moving sum of absolute values incrementally.incrmsumabs2( window )
: compute a moving sum of squared absolute values incrementally.incrmsummary( window )
: compute a moving statistical summary incrementally.incrmsumprod( window )
: compute a moving sum of products incrementally.incrmvariance( window[, mean] )
: compute a moving unbiased sample variance incrementally.incrmvmr( window[, mean] )
: compute a moving variance-to-mean ratio (VMR) incrementally.incrnancount()
: compute a count incrementally, ignoringNaN
values.incrnansum()
: compute a sum incrementally, ignoringNaN
values.incrnansumabs()
: compute a sum of absolute values incrementally, ignoringNaN
values.incrnansumabs2()
: compute a sum of squared absolute values incrementally, ignoringNaN
values.incrpcorr( [mx, my] )
: compute a sample Pearson product-moment correlation coefficient incrementally.incrpcorr2( [mx, my] )
: compute a squared sample Pearson product-moment correlation coefficient incrementally.incrpcorrdist( [mx, my] )
: compute a sample Pearson product-moment correlation distance incrementally.incrpcorrdistmat( out[, means] )
: compute a sample Pearson product-moment correlation distance matrix incrementally.incrpcorrmat( out[, means] )
: compute a sample Pearson product-moment correlation matrix incrementally.incrprod()
: compute a product incrementally.incrrange()
: compute a range incrementally.incrrmse()
: compute the root mean squared error (RMSE) incrementally.incrrss()
: compute the residual sum of squares (RSS) incrementally.incrskewness()
: compute a corrected sample skewness incrementally.incrstdev( [mean] )
: compute a corrected sample standard deviation incrementally.incrsum()
: compute a sum incrementally.incrsumabs()
: compute a sum of absolute values incrementally.incrsumabs2()
: compute a sum of squared absolute values incrementally.incrsummary()
: compute a statistical summary incrementally.incrsumprod()
: compute a sum of products incrementally.incrvariance( [mean] )
: compute an unbiased sample variance incrementally.incrvmr( [mean] )
: compute a variance-to-mean ratio (VMR) incrementally.incrwmean()
: compute a weighted arithmetic mean incrementally.
Examples
var getKeys = require( '@stdlib/utils/keys' );
var ns = require( '@stdlib/stats/incr' );
console.log( getKeys( ns ) );